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Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
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are announcing the position as DDLS PhD student in Data driven evolution and biodiversity. Data driven evolution and biodiversity concerns research that takes advantage of the massive data streams offered by
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pangenomics of polyploids Project description This PhD project investigates how whole-genome duplication reshapes genome evolution using comparative pangenomics across multiple natural diploid–polyploid species
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various IPCC climate scenarios Qualification requirements Appointment to a post-doctoral position requires that the applicant has a PhD in Biology, Ecology, Data Science, or a related subject, or an
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competence in image analysis and data processing. What you will do Develop and optimize experimental workflows, including sample preparation under different environmental conditions. Design and conduct
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cyber resilient AI, promoting education, knowledge sharing, and policy development. This PhD position is associated with the research theme Runtime Security Assurance. Once trained, AI models can be
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algorithms for Bayesian machine learning with applications in e.g., medical image analysis. The doctoral student position is offered within the machine learning project “The Challenges for Machine Learning in